Download Advances in Computing and Information Technology: First by Sundarapandian Vaidyanathan (auth.), David C. Wyld, Michal PDF

By Sundarapandian Vaidyanathan (auth.), David C. Wyld, Michal Wozniak, Nabendu Chaki, Natarajan Meghanathan, Dhinaharan Nagamalai (eds.)

This booklet constitutes the complaints of the 1st foreign convention on Advances in Computing and knowledge know-how, ACITY 2011, held in Chennai, India, in July 2011. The fifty five revised complete papers awarded have been conscientiously reviewed and chosen from a variety of submissions. The papers function major contributions to all significant fields of the pc technology and data know-how in theoretical and useful aspects.

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Umamahesw aril, S. Sumathil,S. Sivanandaml and K. Anburajan, 2007 • Luping Ji and Zhang Yi, 2007 • • • • 12. Xie, 2010 • • Orientation map is calculated and divided into 4 tiles. Homogeneity coefficient is computed for every tile till maximum level has reached. Homogeneity vector constructed is given as input to MultiLayer perceptron for classification. Clustering is performed to divide the database into respective classes. K-means algorithm is used to resolve intra class variability. Continuous classification is performed after clustering to improve the performance of classification.

In this paper we propose a formal syntax for requirements called Adv-EARS. We define a grammar for this syntax such that a requirements document in this format can be grammatically parsed and the prospective actors and use cases are automatically derived from the parse tree. The use case diagram is then automatically generated based on the actors and use cases and their relationships. We have used requirements of an Insurance system as a case study to illustrate our approach. Keywords: Requirements-Engineering, Adv-EARS, Automated Use case derivation, Formal requirements syntax.

Fingerprint Classification using Kohonen Topology map. In: IEEE International Conference on Image Processing, vol. 3, pp. 230–233 (2001) 10. : Automatic Fingerprint Classificaiton Based on Embedded Hidden Markov Models. In: IEEE, International Conference on Machine Learning and Cybernetics, vol. 5, pp. 3033–3038 (2003) 34 D. Parekh and Rekha Vig 11. : Fingerprint Classification using Homogeneity Structure of Fingerprint’s orientation field and Neural Net. In: International Symposium on Image and Signal Processing and Analysis, pp.

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